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Atlas-based prostate segmentation using an hybrid registration

Authors :
Sébastien Martin
Vincent Daanen
Jocelyne Troccaz
Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble - UMR 5525 (TIMC-IMAG)
VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)
INtegrative research unit on Social and Individual DEvelopment (INSIDE)
University of Luxembourg [Luxembourg]
Gestes Medico-chirurgicaux Assistés par Ordinateur (TIMC-IMAG-GMCAO)
VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)
Bourse Doctorale Rgion Rhône-Alpes
cluster ISLE
Source :
International Journal of Computer Assisted Radiology and Surgery, International Journal of Computer Assisted Radiology and Surgery, Springer Verlag, 2008, 3, pp.485-492
Publication Year :
2008
Publisher :
Springer Science and Business Media LLC, 2008.

Abstract

Purpose: This paper presents the preliminary results of a semi-automatic method for prostate segmentation of Magnetic Resonance Images (MRI) which aims to be incorporated in a navigation system for prostate brachytherapy. Methods: The method is based on the registration of an anatomical atlas computed from a population of 18 MRI exams onto a patient image. An hybrid registration framework which couples an intensity-based registration with a robust point-matching algorithm is used for both atlas building and atlas registration. Results: The method has been validated on the same dataset that the one used to construct the atlas using the "leave-one-out method". Results gives a mean error of 3.39 mm and a standard deviation of 1.95 mm with respect to expert segmentations. Conclusions: We think that this segmentation tool may be a very valuable help to the clinician for routine quantitative image exploitation.<br />Comment: International Journal of Computer Assisted Radiology and Surgery (2008) 000-999

Details

ISSN :
18616429 and 18616410
Volume :
3
Database :
OpenAIRE
Journal :
International Journal of Computer Assisted Radiology and Surgery
Accession number :
edsair.doi.dedup.....6e1e2ef772ca9dbe130f178aa3615a3a
Full Text :
https://doi.org/10.1007/s11548-008-0247-0